Andrei Kirilenko

Climate change impacts on forestry

Changing temperature and precipitation pattern and increasing concentrations of atmospheric CO2 are likely to drive significant modifications in natural and modified forests. Our review is focused on recent publications that discuss the changes in commercial forestry, excluding the ecosystem functions of forests and nontimber forest products. We concentrate on potential direct and indirect impacts of climate change on forest industry, the projections of future trends in commercial forestry, the possible role of biofuels, and changes in supply and demand.

Facilitating Content Analysis in Tourism Research

The article proposes a new methodological approach to facilitate content analysis of electronic textual data in a more efficient and transparent way. The textual data are processed iteratively by two software products, CATPAC and WORDER. This approach permits smoothing of the original textual data, identification of the variables of interest, frequency count of the occurrences of these variables in the texts being processed, storage of frequency results in general purpose statistical packages, and subsequent dimensional reduction of word-frequency data by means of factor analysis. Application of this methodology is illustrated on three examples of destination-image studies, which cover content analyses of open-ended responses to e-survey questions, texts from tourism Web sites, and newspaper articles. Advantages and disadvantages of the proposed research technique, its contribution to tourism studies, and the place of the approach within the quantitative paradigm of content analysis are also discussed.

Cultural Differences in Pictorial Destination Images Russia through the Camera Lenses of American and Korean Tourists

Destination photography communicates images that shape and reshape destination perceptions of past and potential tourists and, consequently, influence their decision-making process. Using theoretical underpinnings provided in works on culture, this exploratory study examines whether destination photographs taken by tourists and posted on social-network websites are reflective of culture to which those tourists belong. Content analysis of American and Korean photographs of Russia posted on Flickr and in Korean travel blogs, respectively, was followed by chi-square and co-occurrence analyses of destination attributes, as well as geospatial analysis of image locations using ARC GIS software. Although the core of Russia’s destination image—urban, contemporary, architecturally interesting, and spacious—is similar for both cultural groups, the study found differences in the way that American and Korean tourists represent Russia as a destination. These differences are discussed from the perspective of tourists’ respective cultures.

Fire Drives Transcontinental Variation in Tree Birch Defense against Browsing by Snowshoe Hares

Fire has been the dominant disturbance in boreal America since the Pleistocene, resulting in a spatial mosaic in which the most fire occurs in the continental northwest. Spatial variation in snowshoe hare (Lepus americanus) density reflects the fire mosaic. Because fire initiates secondary forest succession, a fire mosaic creates variation in the abundance of early successional plants that snowshoe hares eat in winter, leading to geographic variation in hare density. We hypothesize that fire is the template for a geographic mosaic of natural selection: where fire is greatest and hares are most abundant, hare browsing has most strongly selected juvenile‐phase woody plants for defense. We tested the hypothesis at multiple spatial scales using Alaska birch (Betula neoalaskana) and white birch (Betula papyrifera). We also examined five alternative hypotheses for geographic variation in antibrowsing defense. The fire‐hare‐defense hypothesis was supported at transcontinental, regional, and local scales; alternative hypotheses were rejected. Our results link transcontinental variation in species interactions to an abiotic environmental driver, fire. Intakes of defense toxins by Alaskan hares exceed those by Wisconsin hares, suggesting that the proposed selection mosaic may coincide with a geographic mosaic of coevolution.

Climate change discourse in mass media: application of computer-assisted content analysis

Content analysis of mass media publications has become a major scientific method used to analyze public discourse on climate change. We propose a computer-assisted content analysis method to extract prevalent themes and analyze discourse changes over an extended period in an objective and quantifiable manner. The method includes the following: (1) sample selection; (2) preparation of the text segments for computer processing; (3) identifying themes in the texts using exploratory factor analysis; (4) combining identified themes into higher order themes using confirmatory factor analysis; (5) using factor scores to interpret themes obtained from public discourse; and (6) tracking the main themes of public discourse through time. We apply the proposed methodology to the analysis of the articles published in the New York Times on climate change during the period from 1995 to 2010. We found a gradual decline in the volume of material within the “Science” topic and an expansion of themes classified under the “Politics” topic.

Weathering the Soviet Countryside: the Impact of Climate and Agricultural Policies on Russian Grain Yields, 1958-2010

Agriculture in Russia has always had to contend with unfavorable climate. At the same time, large-scale socio-economic experiments have also strained the country’s food production potential throughout the 20th century. The relative role of climate and state agricultural policies in affecting production of cereals was studied for the period of 1958–2010. The study used statistical yield modeling to explain the variations in observed yields with slowly changing progress in technology and management and weather variability. The correlation between the actual and weather-explained yields is moderate to high: measured at the level of the entire country, Pearson’s r is 0.74 and Spearman’s rho is 0.68. Further, we suggest that the residual yield variability can be explained partially with the influence of large-scale changes in agricultural policies at the state level. Between these policies, we consider the following key periods in the history of Russian agriculture: “Virgin Lands” campaign (end of 1950s), Kosygin-Liberman initiatives (late 1960s), Brezhnev’s investment programmes in response of stagnation of agriculture (late 1970s – early 1980s), Gorbachev’s “Perestrojka” (1985–1991), and land privatization and price liberalization (1990s).

Inter-Coder Agreement in One-to-Many Classification: Fuzzy Kappa.

Content analysis involves classification of textual, visual, or audio data. The inter-coder agreement is estimated by making two or more coders to classify the same data units, with subsequent comparison of their results. The existing methods of agreement estimation, e.g., Cohen’s kappa, require that coders place each unit of content into one and only one category (one-to-one coding) from the pre-established set of categories. However, in certain data domains (e.g., maps, photographs, databases of texts and images), this requirement seems overly restrictive. The restriction could be lifted, provided that there is a measure to calculate the inter-coder agreement in the one-to-many protocol. Building on the existing approaches to one-to-many coding in geography and biomedicine, such measure, fuzzy kappa, which is an extension of Cohen’s kappa, is proposed. It is argued that the measure is especially compatible with data from certain domains, when holistic reasoning of human coders is utilized in order to describe the data and access the meaning of communication.

Sochi Olympics on Twitter: Topics, Geographical Landscape, and Temporal Dynamics

A successful destination must be favorably positioned in the public mind. Mega-sporting events are an integral part of destination marketing because they attract worldwide visibility and publicity, provide a nucleus for a positively framed public discourse, and have the potential to improve attitudes toward countries and the destinations within them. This study investigates how the Sochi Olympics were portrayed on Twitter by hosts and guests. The study addresses the following questions: What is the geographic landscape of Twitter messages about the Sochi Olympics? What issues were the most salient before, during, and after the games? What are the temporal dynamics of issues concerning the Sochi Olympics? The chapter illustrates an analytical approach to extracting topical, spatial, and temporal information from Twitter messages.

Grassroots Branding with Twitter: Amazing Florida

Social networks sites (SNS) and online communications have revolutionized the way people interact with each other, and these changes have important marketing implications in a number of commercial contexts. In tourism and hospitality context, SNS communications can be considered as electronic word-of-mouth about people’s travel experiences. When SNS data is taken into consideration by destination marketing organizations for branding purposes, the visitors to the destination can be regarded as agents of that destination’s branding effort, and the branding approach as “grassroots” branding. This empirical study explores a suitability of using publicly accessible data from Twitter for gaining visitors’ perceptions about Florida. It examines what positive affective states are associated with the destination and to which destination attributes these affective states are related most closely. Potentially, the study can contribute to developing a non-obtrusive, low-cost, and time-efficient approach to tap into visitors’ experiences and affective states expressed through tweeting.

Evaluation of satellite-derived agro-climate variables in the Northern Great Plains of the United States

The climate of the United States Northern Great Plains region is highly variable. Modelling of agriculture in this region and similar locations depends on the availability and quality of satellite and ground data for agro-climate variables. We evaluated tropical rainfall measuring mission (TRMM) multi-satellite preparation analysis (TMPA) precipitation, atmospheric infrared sounder (AIRS) surface air temperature, and AIRS relative air humidity (RH). A significant bias was found within the temperature and RH products and no bias but an insufficient rain event detection skill in the precipitation product (probability of detection ∼0.3). A linear correction of the temperature product removed the bias as well as lowered the root mean square deviation (RMSD). The bias-corrections for RH led to increased RMSD or worse correlation. For precipitation, the correlation between the satellite product and ground data improved if cumulative precipitation or only precipitation during the growing season was used.