Tourism is one of the largest industries in the world and it continues to grow at a rapid pace. Tourism is dependent upon weather and climate, particularly the length and quality of the outdoor recreation season for nature-based tourism, since it is directly affected by weather. Indirectly, the natural biophysical resources that outdoor tourism is based upon can also be altered by climate. Thus, climate change has the potential to affect nature-based tourism that takes place in national parks and other protected areas. Of the studies that analyse the impacts of climate change in national parks, the vast majority focus on conservation policy and planning rather than tourism. This study applies a single variable regression analysis technique to empirically evaluate the affects of climate change on the quantity and seasonal patterns of visitation to United States national parks under a range of climate change scenarios for the 2020s, 2050s, and 2080s (The Met Office Hadley Centre CM3 B21 (United Kingdom) and Commonwealth Scientific and Industrial Research Organisation MK2B A11 (Australia) climate models were used for the Alaskan parks, and the National Center for Atmospheric Research PCM B21 (United States) and Centre for Climate Systems Research NIES A11 (Japan) models were used for the contiguous states). Fourteen parks are included in the study, representing 12 different climate regimes across the country and 58% of total visitation to all national parks in the United States in 2005. In general, the number of visits to parks in the northern regions of the country, excluding Alaska, is projected to increase annually, with the majority of increases occurring in the spring and fall shoulder seasons. In Alaska, there is no consistent pattern on an annual basis due to projections being calculated for only the low season (winter) for Denali, and for the high season (summer) for Glacier Bay. Based on these projections, visitation may increase during the low season and decrease during the high season for Alaskan parks. Parks in the south are projected to experience decreased annual visitation as temperatures become uncomfortably hot, particularly under high emissions scenarios. The largest changes in visitation are projected to occur in the 2080s, although some parks may experience noticeable changes as early as the 2020s in particular seasons. Small to moderate changes in visitation (up to 10% annually) are projected with the low emission climate change scenarios, even into the 2080s. Small to large visitation changes (up to 47% annually) are projected using the higher emission climate change scenarios. These visitation changes could lead to the need for substantial management changes in certain US national parks as revenue collected from user fees and operational costs are altered. Additional ecological and social impacts resulting from increased visitation will also need to be critically considered. Where fewer visits are projected, decreased revenue may lead to an inability to properly manage the park. The results of the study can be used by the National Park Service and regional and park managers to plan for visitation changes that might occur as climate change continues over the 21st century.

This thesis investigates changes in temperature extremes between 1950-2005, analysing gridded data sets of observations and climate model simulations. It focuses on changes in the frequency of extreme temperatures occurring in single days or over periods of six or more consecutive days. The study aims to quantify the significance of changes in extreme temperature events and answer the following questions. Are external or human-induced forcings together with natural forcings responsible for the observed change in temperature extremes or can these changes be explained due to natural climate variability alone? Are the observed changes consistent with those from climate model simulations? And are the changes in extremes linked only to changes in the mean climate, or only to those in climate variability or both? The analysis concentrates on changes from global to regional scale and from annual mean to seasonal scale. A detection method is applied to assess if changes are significantly different with respect to the internal climate variability. Results show that there has been a significant increase in warm daily extremes and a decrease in cold ones, both on large and small spatial scales. The increase in warm extremes has been found to be highly correlated with the increase in mean temperature. The changes in daily extremes are well represented in climate model simulations. Changes in the persistent extremes show a detectable increase in the frequency of warm and a decrease in cold events and are reproducible by models.

Amazonia contains the largest expanse of tropical forest in the world and is globally significant as a store of carbon, a regulator of climate and an area of high species diversity. The ability of the Amazonian forests to maintain these important ecological functions is however, increasingly under question in light of recent predictions of climate change. There is currently significant uncertainty in model predictions of how Amazonian forests will respond to predicted future climate change. This thesis reports the finding of two field studies, targeted at understanding the responses of two tropical forest carbon fluxes which are poorly simulated in vegetation models, and two modelling studies, which aim to better quantify uncertainty on model predictions of the effects of current and future climate change on the ecological function of Amazonian forests. The responses of forests to varying magnitudes of seasonal changes in climate which occur across Amazonia can give an important insight into the sensitivity of these forests to climate perturbations and changes. Testing the sensitivity of an Amazonian forest in Tambopata, Peru, to seasonal variations in precipitation and temperature, I find that the stem diameter growth of tropical trees is more sensitive to water availability than temperature changes. The vulnerability of trees to reduced soil water varied between tree classes with different functional traits, including wood density, tree height, tree diameter and tree growth rate. Similarly, I find that the respiration flux from tropical dead wood, at a second site in French Guiana, is highly sensitive to variations in water content. I show that these variations in respiration fluxes can be modelled successfully using seasonal variations in soil water content. To date there are few studies which have comprehensively tested vegetation models using ecological data from Amazon forests. Using data assimilation and nine sources of ecological data I estimate the certainty with which we can parameterise a carbon cycle model to represent the effects of a strong dry season on tropical forests. Using this technique I find, that the carbon balance of Amazonian forests can be very sensitive to reductions in water availability, and that these seasonal changes need to be accurately simulated across models to correctly predict annual carbon budgets. The variability in model responses caused by differences in the way processes are structured and parameterised in vegetation models requires better quantification. Using a model inter-comparison I demonstrate that the relative sensitivity of modelled climate-vegetation feedbacks to changes in ambient air temperature and precipitation is highly variable. I find that although the models showed similar directional responses at both the leaf and canopy scale some models showed a greater sensitivity to temperature and others to drought. I therefore demonstrate the need for greater constraint on modelled responses of Amazonian forests to changes in temperature and precipitation. The impact of climate change on Amazonian forests is an important global issue, yet our knowledge is reliant on our ability to understand the uncertainties on our predictions. Using field data to evaluate and to develop model predictions is a valuable way to reduce the uncertainty associated with modelling future change. This thesis presents an investigation of how tropical forests respond to changes in climate and with what certainty we can model these changes in order to predict the response of Amazon forests to predicted future climate change.

No description available.

Vegetation dominated by heather and bracken, two common species of the UK uplands, is often nutrient limited and heavily influenced by climate. Thus, changes in climate or nutrient availability might be expected to have pronounced effects on growth and competition between these species. Mature heather and bracken turfs, transplanted from the field into 1 x 1 by 0.5 m deep plots, were subjected to factorial experimental treatments of root competition, shoot competition, summer drought, increased nitrogen supply and increased temperature for four consecutive years. The effects of root competition on the growth of heather and bracken were as great as those caused by the environmental treatments alone. Shoot competition had little effect on the growth of the two species, and thus, competition was concluded to occur predominately for below ground resources. Heather, in the building phase, was a superior competitor to bracken due to its extremely fine and invasive root system. Heather was able to compete with and deplete water from the roots of established bracken plants. Measurement of integrated of water use efficiency () and water use by droughted heather and bracken showed that the predicted environmental change scenarios are likely to cause an increase in the intensity of competition for water. There was no evidence of competition for nitrogen, despite nitrogen clearly limiting the growth of both species. The effects of the treatments on shoot phenology, morphology, photosynthetic physiology, biomass and below ground biomass have been examined. Above ground, heather was more responsive to the treatments imposed than bracken, having greater increases in shoot growth in favourable conditions, but greater decreases in shoot growth, and greater physiological acclimation, in stressed conditions, particularly drought in combination with increased nitrogen supply. Below ground, growth of bracken was extremely responsive whilst that of heather was not. However, even when bracken below ground growth was most stimulated, by increased nitrogen supply, it was still held in check by heather.

The aim of this thesis was to investigate soil and environmental factors which influence the adsorption of DOC in upland, moorland soils. In Chapter 1 climate change, the greenhouse effect and the global carbon cycle are discussed briefly. A more detailed discussion of carbon cycling in the plant-soil-water system focuses on DOC retention in podzols and the review concludes with a summary of the aims of this thesis. A peaty podzol has greater potential to retain DOC than the other major soil types within the Glen Dye catchment, N.E. Scotland. Retention of DOC by physico-chemical surface interactions occurred in the mineral horizons of the soil where locally high concentrations of amorphous Fe and Al were present. Laboratory experiments using potassium hydrogen phthalate as a source of DOC showed that DOC retention is favoured by longer contact times between soil and solution. Net retention of DOC in the podzol profile is decreased by increasing the solution pH and by repeated wetting/drying and freezing/thawing cycles. As temperature and reaction time increased, respiration becomes more important as a mechanism for depleting solution phthalate DOC concentrations. Annual fluxes of DOC in precipitation, podzolic O, E and Bs soil horizon solution and stream water were estimated for the Burn of Waterhead catchment to be 35, 121, 83, 37 and 48 kg C ha-1yr-1 respectively. The DOC fluxes and the concentrations of related elements varied seasonally, with the largest DOC fluxes produced in the autumn and lowest in the summer. The annual DOC flux from the Burn of Waterhead was lower than fluxes from other catchments at Glen Dye. Results from the field site supported laboratory experimental results which suggested that climate change will result in an increase in the DOC flux from results which suggested that climate change will result in an increase in the DOC flux from peaty podzolic soil.

<p> Consumers often must choose between mutually exclusive products or beliefs related to products, such as to believe or ignore social and environmental causes. Cognitive dissonance (CD) (Festinger, 1957) is a common psychological discomfort that must be resolved, when experienced between inconsistent beliefs, attitudes, or choices. Advertising and marketing promotion to influence consumer decision making often uses celebrity / expert endorsers (Hollensen &amp; Schimmelpfennig, 2013) to improve brand effectiveness and increase sales, yet how endorsements affect consumer attitudes and CD has not been explored. </p><p> During an attempt to revise models of predicting consumer behavior to include CD measurement (e.g., theory of reasoned action in Ajzen &amp; Fishbein, 1980; theory of planned behavior in Ajzen, 1991) it was noted that attempts to add scales to measure social norms improved model effectiveness. Moreover, attempts to measure CD (e.g., Cassel &amp; Chow, 2002; Elliot &amp; Devine, 1994; Hausknecht, Sweeney, Soutar, &amp; Johnson, 1998; Sakai, 1999; Shultz &amp; Lepper, 1996; and Sweeney, Hausknecht, &amp; Soutar, 2000) did not measure the social context of CD as originally conceived by Festinger to explain illogical behaviors given observable facts such as cigarette smoking and cult activities, etc. After review of the CD phenomenon and its common origins in Lewin (1936, 1951), Osgood and Tannenbaum (1955), Heider (1946, 1958), and Festinger (1954, 1957), it was discovered that CD is a multivariate phenomenon and more complex than existing models of decision making or measurement instruments could accommodate. </p><p> This dissertation derived a CD instrument with semantic differential scales from congruity theory (Osgood &amp; Tannenbaum, 1955) and balance theory (Heider, 1946, 1958) to measure multivariate CD during attitude change using endorsement by former U.S. Vice President Albert Gore, Jr. of an important social cause: global warming. With a repeated measures procedure, CD was induced using a social comparison referent (SCR) of Mr. Gore for a snowball sample of 567 respondents recruited from online political groups and social media websites. Information about global warming was presented within simulated news headlines to 16 randomly assigned groups of 567 respondents with alternating combinations of positively / negatively toned messages, high credibility / low credibility publications, and domestic-attributed research / foreign-attributed research. The instrument was tested for sensitivity, validity, and reliability. </p><p> The results indicated that when presented with information in opposition to their original opinion, regardless of their view of the endorser SCR&rsquo;s opinion, respondents, in this order: 1. Changed their perception of the endorser&rsquo;s attitude toward global warming (termed social meaning in this dissertation); 2. Changed their view of the value of the endorser&rsquo;s opinion (i.e., referent meaning); and, lastly, 3. Changed their own opinion on global warming (i.e., object meaning). </p><p> This dissertation demonstrated that due to the effect of CD, attitude measurement of an endorsement can be improved by adding additional scales to measure the perceived social context (i.e., a social comparison referent [SCR]) of the endorsement. Evidence has shown that to change a consumer attitude toward a belief or product, the mediating effect of the endorser SCR on the attitude should be considered. The presence of the endorser SCR shows the relationship between congruity theory and balance theory, and is evidence that Lewin&rsquo;s (1936) topological psychology suggested examination of the social context of attitude measurement will increase accuracy in estimating behavior. Measurement of the SCR is an important step in attitude measurement to minimize the effect of unintended or unknown social comparison threats to internal validity on measurement scales.</p>

<p> A mechanistic understanding of the North American Monsoon (NAM) is suggested by incorporating local- and synoptic-scale processes. The local-scale mechanism describes the effect sea surface temperature (SST) in Gulf of California (GC) and how it contributes to the low-level moisture during the 2004 NAM. Before NAM onset, the strong low-level temperature inversion exists over the GC, but this inversion weakens with increasing GC SST and generally disappears once SSTs exceed 29.5&deg;C, allowing the moist air, trapped in the MBL, to mix with free tropospheric air. This leads to a deep, moist layer that can be transported toward the NAM regions to produce thunderstorms. The synoptic scale mechanism is based on climatologies from 1983 to 2010 and explains that the warmest SSTs moving up the coast contributes to NAM convection and atmospheric heating, and consequently advancing the position of the anticyclone and the region of descent northward. </p><p> In order to improve microphysical properties of ice clouds, this study develops self-consistent second order polynomial mass- and projected area-dimension (m-D and A-D) expressions that are valid over a much larger size range, compared to traditional power laws. Such expressions can easily be reduced to power laws for the size range of interest, in order to use in cloud and climate models. This was done by combining field measurements of individual ice particle m and D with airborne optical probe measurements of D, A and estimates of m. The resulting m-D and A-D expressions are functions of temperature and cloud type (synoptic vs. anvil), and are in good agreement with m-D power laws developed from recent field studies. These expressions also appear representative for heavily rimed dendrites occurring over the Sierra Nevada Mountains. By using the m-D field measurements of rimed and unrimed particles, and by developing theoretical methods, an approach was suggested for calculating rimed m and A, which has the benefit of accounting for the degree of riming, and therefore it produces a gradual and continuous growth from unrimed ice particles to graupel. The treatment for riming includes a parameterization for collision efficiency as a function of droplet size and ice particle size using the available numerical studies. </p><p> A rimed snow growth model (RSGM) was developed based on the growth processes of vapor diffusion, aggregation, and riming. The RSGM uses a measured radar reflectivity at cloud top for initialization, and then predicts the vertical evolution of size spectra. The RSGM is based on the zeroth- and second- moment conservation equations with respect to mass, and thus conserves the number concentration and radar reflectivity, respectively. The size spectra predicted by the RSGM are in good agreement with observed spectra during Lagrangian spiral descents through frontal clouds. The snowfall rate with the inclusion of riming is significantly greater than that produced by the vapor deposition and aggregation alone. Snowfall rates are found to be sensitive to the cloud drop size distribution.</p>

The variability of atmospheric circulation is reconstructed over the last two centuries from surface pressure observations extending into the 18th and 19th centuries at 51 locations across Europe. Daily observations from London and Paris exist for 1697-1706; these are analyzed and compared to modem data. The monthly pressure data have been rigorously checked to ensure compatibility with modem observational standards. The pressure series have undergone relative homogeneity tests using a technique developed to deal specifically with these data, and the results compared to those obtained using well-established homogeneity methods. The method developed here was shown to be the most appropriate, particularly for the earlier data. Empirical orthogonal function (BOF) analysis was used to test the stability of circulation patterns over different periods. The three most important modes of variation were found: EOF 1) describing the overall covariance of pressure; EOF 2) the strength of the zonal flow over Europe; and EOF 3) the degree of cycloncity or anti-cyclonicity in the eastern North Atlantic. The ability of the sparser network of 20 stations available from the early 19th century to adequately recover the patterns and variability of the full network is demonstrated. Time series of the North Atlantic Oscillation, the mid-latitude westerly winds, and an index representing the strength of the westerly air flow between London and Paris have been constructed and extend back to the 18th century, as well as the period 1697-1706 for Paris and London. Correlations between eight temperature series from western and central Europe and the circulation indices demonstrate the importance of the atmospheric circulation in determining European temperatures. Running correlations calculated over windows of 25 years reveal striking non-stationarity in circulation-climate relationships. Spectral analyses of the circulation indices suggest a shift from high-frequency oscillatory behaviour in the 19th century to lower frequency behaviour in the 20th

Climate change imposes major threats for farming communities in South Asia as increased temperatures and changes in precipitation impact yields. Local farmers in Pakistan are facing similar challenges and the country has already been highly affected by climate change. Further, local knowledge is increasingly being recognized as an important complement to quantitative climate data. There is a need to go beyond the quantitative results in climate change research, and ground proof these data by including local experiences. Many farmers around the world are experiencing climate change and are responding to these with various adaptation strategies. This study examines climate change in the Gujrat and Jhelum districts in the Punjab province in Pakistan, how local farmers perceive climate change and what adaptation strategies local farmers have implemented. The study also intends to examine the main constraints to adaptation by incorporating expert views to analyze issues and gaps in the system. The results show increased temperatures and decreased precipitation in the study region between 1975-2014. Farmer surveys indicate that a majority of the farmers perceive these changes and have applied different adaptation strategies as a response. These strategies mainly consist of: changing planting/sowing time and increased irrigation using groundwater. A third form of response to smaller yields and decreased income was alternative off- farm jobs, as an additional income. Expert interviews reveal contradictions of implementation of climate change adaptation policies along with contrasting responses to the farmers regarding institutional efforts to support the local farmers. These results show how lack of institutional support is hindering effective, successful and long-term adaptation for these farming communities.