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PubMed2003

Influence of climatic conditions on the irritant patch test with sodium lauryl sulphate.

Irritant patch testing with detergents is increasingly being used as a measure of skin barrier function, but there is evidence that climatic changes can influence the test outcome. In this study we investigated the relation between cutaneous reactivity to a detergent and climatic conditions. Between January 2000 and December 2001 epicutaneous patch testing with 0.5% sodium lauryl sulphate was performed on the forearm of 487 volunteers and evaluated by measuring transepidermal water loss (TEWL). Atopic individuals were excluded. Climatic conditions recorded by the German Meteorological Service were then compared with the test outcome. Climatic measurements 7 days before evaluation of the patch test were used to calculate an arbitrary mean value for each climatic parameter. A strong correlation was observed between temperature, steam pressure, absolute and relative humidity and the increase in TEWL, and most pronounced during winter and spring. The data provide experimental confirmation of epidemiological studies in which the incidence of irritant skin changes was found to be increased during the winter season with cold and dry air. For the first time, two formulae for adjusting TEWL values according to climatic conditions are presented. It is possible with these formulae to compare between a measured TEWL value and a calculated value.

Adolescent↗
PubMed2004

Geographical variations in heart deaths and diabetes: effect of climate and a possible relationship to magnesium.

BACKGROUND: Geographical variations in deaths from heart disease and the prevalence of diabetes occur in the United States. METHODS: These geographical variations, by state, were compared to the tertiles of the Z-score (Z-climate) obtained from the mean annual temperature and precipitation, by state, and to the tertiles of the Z-score (Z-environment) obtained from six environmental factors, by state, in monovariant analyses of variance. RESULTS: Both Z-scores were significantly related to male heart deaths (Z-climate: p = 0.000009; Z-environment: p = 0.000043) with Z-climate being the most significant. Both Z-scores were significantly related to the 1998 prevalence of diabetes (Z-climate: p = 0.00018; Z-environment: p = 0.0059) with the climate again being the most significant. CONCLUSIONS: Increased temperature can increase magnesium sweat losses, which may not be compensated by diet or water intake. Climate relationships to these diseases need further investigation.

Adult↗
PubMed2000

Climate change and the adaptability of agriculture: a review.

The assessment of climate change impacts on agriculture has emerged as a recognizable field of research over the past 15 years or so. In a relatively short period, this area of work has undergone a number of important conceptual and methodological developments. Among many questions that have been debated are the adaptability of agriculture to climate change and the importance of land management adjustments in reducing the adverse effects of climate change. In turn, this latter focus has spawned a discussion regarding the nature of adaptation and the ability of agriculture to respond to sudden and rapid climatic changes. In this paper we present an overview of this debate. It is argued that the first generation of climate change impact studies generally ignored the possibility that agriculturalists may adjust their farming practices in order to cope with climate change or to take advantage of new production opportunities. This conceptual oversight has been largely eliminated over the past five years or so. However, questions remain surrounding the likelihood that various adaptive strategies will actually be deployed in particular places. In this paper, we stress the importance of studying adaptation in the context of decision-making at the individual farm level and beyond.

Agriculture↗
PubMed2005

Genetic variation in Echinacea angustifolia along a climatic gradient.

BACKGROUNDS AND AIMS: Echinacea angustifolia is a widespread species distributed throughout the Great Plains region of North America. Genetic differentiation among populations was investigated along a 1500 km north-south climatic gradient in North America, a region with no major geographical barriers. The objective of the study was to determine if genetic differentiation of populations could be explained by an isolation-by-distance model or by associations with climatic parameters known to affect plant growth and survival. METHODS: Historical climatic data were used to define the nature of the climatic gradient and AFLP markers were used to establish patterns of population genetic differentiation among ten Echinacea populations collected from North Dakota to Oklahoma. A total of 1290 fragments were scored using six EcoRI/MseI and three PstI/MseI primer combinations. Assessment of the correlation between climatic, genetic and geographic distances was assessed by Mantel and partial Mantel tests. KEY RESULTS: PstI/MseI combinations produced significantly fewer fragments, but a larger percentage was unique compared with EcoRI/MseI markers. Using estimates of F(ST), populations in Oklahoma and southern Kansas were identified as the most divergent from the other populations. Both the neighbour-joining tree and principal co-ordinate analysis clustered the populations in a north-south spatial orientation. About 60% of the genetic variation was found within populations, 20% among populations and the remaining 20% was partitioned among groups that were defined by the topology of the neighbour-joining tree. Significant support was found for the isolation-by-distance model independent of the effects of annual mean precipitation, but not from annual mean temperature and freeze-free days. CONCLUSIONS: Echinacea angustifolia populations exhibit genetic divergence along a north-south climatic gradient. The data support an isolation-by-distance restriction in gene flow that is independent of annual mean precipitation.

Adaptation, Physiological↗
PubMed2025

Evolutionary Genomics Unravels the Responses and Adaptation to Climate Change in a Key Alpine Forest Tree Species.

Despite widespread biodiversity loss, our understanding of how species and populations will respond to accelerated climate change remains limited. In this study, we integrate population genomics, experimental evolution, and environmental modeling to elucidate the evolutionary responses to climate change in Populus lasiocarpa, a key alpine forest tree species primarily distributed in the mountainous regions of a global biodiversity hotspot. Over historical timescales, our findings demonstrate that demographic dynamics, divergent selection, and long-term balancing selection have shaped and maintained genetic variation within and between populations. In examining genomic signatures of contemporary climate adaptation, we found that haplotype blocks, potentially caused by inversion polymorphisms that suppress recombination, are linked to enriched combinations of locally adaptive environmental variations. We further assessed the relative contributions of environmentally induced plastic responses, constitutive expression divergence between genetic clusters, and their interactions in driving gene expression variation and divergence. Notably, we observed a strong correlation between sequence divergence and constitutive differential expression among genetic clusters. Finally, by incorporating genetic adaptation, migration, and genetic load into our predictions of population-level climate change risks, we identified western populations-primarily distributed in the Hengduan Mountains, a region known for its environmental heterogeneity and significant biodiversity-as the most vulnerable to climate change. These populations should be prioritized for conservation and management. Overall, our study advances the understanding of the relative roles of long-term natural selection, local environmental adaptation, and immediate plastic expression changes in shaping the responses of natural populations of keystone species to climate change.

Climate Change↗
PubMed2003

Partitioning interannual variability in net ecosystem exchange between climatic variability and functional change.

Interannual variability (IAV) in net ecosystem exchange of carbon (NEE) is a critical factor in projections of future ecosystem changes. However, our understanding of IAV is limited because of the difficulty in isolating its numerous causes. We proposed that IAV in NEE is primarily caused by climatic variability, through its direct effects on photosynthesis and respiration and through its indirect effects on carbon fluxes (i.e., the parameters that govern photosynthesis and respiration), hereafter called functional change. We employed a homogeneity-of-slopes model to identify the functional change contributing to IAV in NEE and nighttime ecosystem respiration (RE). The model uses multiple regression analysis to relate NEE and RE with climatic variables for individual years and for all years. If the use of different slopes for each year significantly improves the model fitting compared to the use of one slope for all years, we consider that functional change exists, at least on annual time scales. With the functional change detected, we then partition the observed variation in NEE or RE to four components, namely, the functional change, the direct effect of interannual climatic variability, the direct effect of seasonal climatic variation, and random error. Application of this approach to a data set collected at the Duke Forest AmeriFlux site from August 1997 to December 2001 indicated that functional change, interannual climatic variability, seasonal climatic variation and random error explained 9.9, 8.9, 59.9 and 21.3%, respectively, of the observed variation in NEE and 13.1, 5.0, 38.1 and 43.8%, respectively, of the observed variation in RE.

Carbon Dioxide↗
PubMed2001

The timing of life-history events in a changing climate.

Although empirical and theoretical studies suggest that climate influences the timing of life-history events in animals and plants, correlations between climate and the timing of events such as egg-laying, migration or flowering do not reveal the mechanisms by which natural selection operates on life-history events. We present a general autoregressive model of the timing of life-history events in relation to variation in global climate that, like autoregressive models of population dynamics, allows for a more mechanistic understanding of the roles of climate, resources and competition. We applied the model to data on 50 years of annual dates of first flowering by three species of plants in 26 populations covering 4 degrees of latitude in Norway. In agreement with earlier studies, plants in most populations and all three species bloomed earlier following warmer winters. Moreover, our model revealed that earlier blooming reflected increasing influences of resources and density-dependent population limitation under climatic warming. The insights available from the application of this model to phenological data in other taxa will contribute to our understanding of the roles of endogenous versus exogenous processes in the evolution of the timing of life-history events in a changing climate.

Anemone↗
PubMed2002

Population dynamics of a South American rodent: seasonal structure interacting with climate, density dependence and predator effects.

Understanding the role of interactions between intrinsic feedback loops and external climatic forces is one of the central challenges within the field of population ecology. For rodent dynamics, the seasonal structure of the environment necessitates changes between two stages: reproductive and non-reproductive. Nevertheless, the interactions between seasonality, climate, density dependence and predators have been generally ignored. We demonstrate that direct climate effects, the nonlinear effect of predators and the nonlinear first-order feedback embedded in a seasonal structure are key elements underlying the large and irregular fluctuations in population numbers exhibited by a small rodent in a semi-arid region of central Chile. We found that factors influencing population growth rates clearly differ between breeding and non-breeding seasons. In addition, we detected nonlinear density dependencies as well as nonlinear and differential effects of generalist and specialist predators. Recent climatic changes may account for dramatic perturbations of the rodent's population dynamics. Changes in the predator guild induced by climate are likely to result, through the food web, in a large impact on small rodent demography and population dynamics. Assuming such interactions to be typical of ecological systems, we conclude that appropriate predictions of the ecological consequences of climate change will depend on having an in-depth understanding of the community-weather system.

Animals↗
PubMed2004

Climate change and evolving human diversity in Europe during the last glacial.

A link between climate change and human evolution during the Pleistocene has often been assumed but rarely tested. At the macro-evolutionary level Foley showed for hominids that extinction, rather than speciation, correlates with environmental change as recorded in the deep sea record. Our aim is to examine this finding at a smaller scale and with high-resolution environmental and archaeological archives. Our interest is in changing patterns of human dispersal under shifting Pleistocene climates during the last glacial period in Europe. Selecting this time frame and region allows us to observe how two hominid taxa, Neanderthals and Crô-Magnons, adapted to climatic conditions during oxygen isotope stage 3. These taxa are representative of two hominid adaptive radiations, termed terrestrial and aquatic, which exhibited different habitat preferences but similar tolerances to climatic factors. Their response to changing ecological conditions was predicated upon their ability to extend their societies in space and time. We examine this difference further using a database of all available radiocarbon determinations from western Europe in the late glacial. These data act as proxies for population history, and in particular the expansion and contraction of regional populations as climate changed rapidly. Independent assessment of these processes is obtained from the genetic history of Europeans. The results indicate that climate affects population contraction rather than expansion. We discuss the consequences for genetic and cultural diversity which led to the legacy of the Ice Age: a single hominid species, globally distributed.

Adaptation, Biological↗
PubMed2004

Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation.

The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations.

Atmosphere↗
PubMed2004

Global climate and the distribution of plant biomes.

Biomes are areas of vegetation that are characterized by the same life-form. Traditional definitions of biomes have also included either geographical or climatic descriptors. This approach describes a wide range of biomes that can be correlated with characteristic climatic conditions, or climatic envelopes. The application of remote sensing technology to the frequent observation of biomes has led to a move away from the often subjective definition of biomes to one that is objective. Carefully characterized observations of life-form, by satellite, have been used to reconsider biome classification and their climatic envelopes. Five major tree biomes can be recognized by satellites based on leaf longevity and morphology: needleleaf evergreen, broadleaf evergreen, needleleaf deciduous, broadleaf cold deciduous and broadleaf drought deciduous. Observations indicate that broadleaf drought deciduous vegetation grades substantially into broadleaf evergreen vegetation. The needleleaf deciduous biome occurs in the world's coldest climates, where summer drought and therefore a drought deciduous biome are absent. Traditional biome definitions are quite static, implying no change in their life-form composition with time, within their particular climatic envelopes. However, this is not the case where there has been global ingress of grasslands and croplands into forested vegetation. The global spread of grasses, a new super-biome, was probably initiated 30-45 Myr ago by an increase in global aridity, and was driven by the natural spread of the disturbances of fire and animal grazing. These disturbances have been further extended over the Holocene era by human activities that have increased the land areas available for domestic animal grazing and for growing crops. The current situation is that grasses now occur in most, if not all biomes, and in many areas they dominate and define the biome. Croplands are also increasing, defining a new and relatively recent component to the grassland super-biome. In the case of both grassland and croplands, various forms of disturbance, particularly frequent disturbance, lead to continued range extensions of the biomes.

Climate↗
PubMed2005

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact.

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10 degrees N-17 degrees N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel-Guillot-Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10-50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level.

Africa, Western↗
PubMed2005

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice.

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate-crop-economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based 'discussion support systems' contribute to learning and farmer-researcher dialogue. Integrated climate-crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis.

Climate↗
PubMed2005

Crop responses to climatic variation.

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal resolution. This paper demonstrates the impacts of climate variability for crop production in a number of crops. Increasing temperature and precipitation variability increases the risks to yield, as shown via computer simulation and experimental studies. The issue of food quality has not been given sufficient importance when assessing the impact of climate change for food and this is addressed. Using simulation models of wheat, the concentration of grain protein is shown to respond to changes in the mean and variability of temperature and precipitation events. The paper concludes with discussion of adaptation possibilities for crops in response to drought and argues that characters that enable better exploration of the soil and slower leaf canopy expansion could lead to crop higher transpiration efficiency.

Acclimatization↗
PubMed2004

Evolutionary potential of Chamaecrista fasciculata in relation to climate change. II. Genetic architecture of three populations reciprocally planted along an environmental gradient in the great plains.

Climate change will test the evolutionary potential of populations. Information regarding the genetic architecture within and among populations is essential for prediction of evolutionary outcomes. However, little is known about the distribution of genetic variation for relevant traits in natural populations or alteration of genetic architecture in a changing environment. In this study, pedigreed families from three populations of the annual prairie legume Chamaecrista fasciculata were reciprocally transplanted in three environments across a broad latitudinal range in the Great Plains. The underlying premise of this work is that northern populations will in the future experience climates similar to current-day climates further south. Estimates of narrow-sense heritability ranged from 0.053 to 0.481, suggesting the potential for evolutionary change is possible for most traits. In general, the northern population harbored less genetic variation and had lower heritability for traits than the southern population. This population also experienced large reductions in fitness, as measured by estimated lifetime fecundity, when raised in either the intermediate or the southern climate, whereas the difference between the intermediate and southern population was less extreme. For fecundity, the pattern of cross-environment additive genetic correlations was antagonistic to evolutionary change in four of six cases when native and nonnative sites were compared. Six additional antagonistic positive correlations were found for the rate of phenological development and leaf thickness. Overall, the data suggest that if climate changes as predicted, the northern population will face a severe evolutionary challenge in the future because of low heritabilities, cross-environment genetic correlations antagonistic to selection, and demographic instability due to lower seed production in a hotter and drier climate.

Adaptation, Physiological↗
PubMed2004

Exploring 30 years of malaria case data in KwaZulu-Natal, South Africa: part II. The impact of non-climatic factors.

Malaria transmission is a multifactorial phenomenon. Climate is a major limiting factor in the spatial and temporal distribution of malaria, but many non-climatic factors may alter or override the effect of climate. Thirty years of monthly malaria incidence data from KwaZulu-Natal province, South Africa, reveal strong medium and long-term trends, which were not present in the climate data. This paper explores various non-climatic factors that may have contributed towards the observed trends. The development of antimalarial drug resistance, available information on human immunodeficiency virus (HIV) prevalence, cross-border people movements, agricultural activities, emergence of insecticide resistance and the case reporting system are reviewed and their potential effect on malaria transmission examined. Single-variable linear regression analysis showed significant association between seasonal case totals (log-transformed) and the measured level of drug resistance (log-transformed) (r2=0.558, n=10, P=0.013) as well as relative measures of HIV infection since 1990 (r2=0.846, n=11, P=0.001). The other factors appear to have affected the level of malaria transmission at certain periods and to some degree. The importance of surveillance and inclusion of non-climatic variables in analysis of malaria data is demonstrated.

Agriculture↗
PubMed2006

Long-term change in the sensitivity of tree-ring growth to climate forcing in Larix decidua.

Tree rings are widely used long-term proxy data which, if combined with long-term instrumental climate records, can provide excellent information on global climate variability. This research aimed to determine whether interannual climate-growth responses in Alpine treeline forests are stationary over time. We used tree-ring width chronologies of Larix decidua (European larch) from 17 sites and monthly temperatures and precipitation data for the period 1800-1999. Climate-growth relationships were assessed with correlation and response functions, and their stationarity and consistency over time were measured using moving correlation. Tree-ring chronologies showed similar interannual variations over the last two centuries, suggesting that the same climatic factors synchronously limited growth at most sites. The most sensitive variables showed significant transient responses varying within the time period, indicating a possible deviation from the uniformitarian principle applied to dendroclimatology. If these findings are confirmed in future studies on other species and in other regions, we suggest that time-dependent variables should be taken into account to avoid overestimation of treeline advance, future forest carbon storage in temperature-limited environments and inaccurate reconstruction of past climate variability.

Carbon↗
PubMed2006

The interplay between climate variability and density dependence in the population viability of Chinook salmon.

The viability of populations is influenced by driving forces such as density dependence and climate variability, but most population viability analyses (PVAs) ignore these factors because of data limitations. Additionally, simplified PVAs produce limited measures of population viability such as annual population growth rate (lamda) or extinction risk. Here we developed a "mechanistic" PVA of threatened Chinook salmon (Oncorhynchus tshawytscha) in which, based on 40 years of detailed data, we related freshwater recruitment of juveniles to density of spawners, and third-year survival in the ocean to monthly indices of broad-scale ocean and climate conditions. Including climate variability in the model produced important effects: estimated population viability was very sensitive to assumptions of future climate conditions and the autocorrelation contained in the climate signal increased mean population abundance while increasing probability of quasi extinction. Because of the presence of density dependence in the model, however we could not distinguish among alternative climate scenarios through mean lamda values, emphasizing the importance of considering multiple measures to elucidate population viability. Our sensitivity analyses demonstrated that the importance of particular parameters varied across models and depended on which viability measure was the response variable. The density-dependent parameter associated with freshwater recruitment was consistently the most important, regardless of viability measure, suggesting that increasing juvenile carrying capacity is important for recovery.

Animals↗