Sustainability of winter tourism in a changing climate over Kashmir Himalaya

Mountain areas are sensitive to climate change. Implications of climate change can be seen in less snow, receding glaciers, increasing temperatures, and decreasing precipitation. Climate change is also a severe threat to snow-related winter sports such as skiing, snowboarding, and cross-country skiing. The change in climate will put further pressure on the sensitive environment of high mountains. Therefore, in this study, an attempt has been made to know the impact of climate change on the snow precipitation, water resources, and winter tourism in the two famous tourist resorts of the Kashmir Valley. Our findings show that winters are getting prolonged with little snow falls on account of climate change. The average minimum and maximum temperatures are showing statistically significant increasing trends for winter months. The precipitation is showing decreasing trends in both the regions. A considerable area in these regions remains under the snow and glacier cover throughout the year especially during the winter and spring seasons. However, time series analysis of LandSat MODIS images using Normalized Difference Snow Index shows a decreasing trend in snow cover in both the regions from past few years. Similarly, the stream discharge, comprising predominantly of snow- and glacier-melt, is showing a statistically significant declining trend despite the melting of these glaciers. The predicted futuristic trends of temperature from Predicting Regional Climates for Impact Studies regional climate model are showing an increase which may enhance snow-melting in the near future posing a serious threat to the sustainability of winter tourism in the region. Hence, it becomes essential to monitor the changes in temperature and snow cover depletion in these basins in order to evaluate their effect on the winter tourism and water resources in the region.     

Reconsidering the Dynamic Interaction of Renewable Resources and Population Growth: A Focus on Long-Run Sustainability

Within the framework of a general equilibrium model we study the long-run dynamics of resources and population if the growth rate of resources and population and the share of labor devoted to production are adversely affected by resource scarcity. Our results show that sustainability, i.e. a positive value of resources and population in the long run, essentially depends on the level of per capita resources at which these feedback mechanisms become active. A detailed bifurcation analysis evidences the richness of possible long-run dynamics.     

Comparing impacts across climate models

In this paper we combine a climate-forecasting model, COSMIC, with a global impact model, GIM, to compare the market impacts of climate change projected by 14 general circulation models. Given a specific date (2100), carbon dioxide concentration (612 ppmv), and global temperature sensitivity (2.5°C), predicted impacts to economies are calculated using climate-response functions from Experimental and Cross-sectional evidence. The Cross-sectional impact model predicts small global benefits across all climate models, whereas the Experimental impact model predicts a range from small benefits to small damages. High-latitude countries are less sensitive to temperature increases than low-latitude countries because they are currently cool. Uniform global temperature changes overestimate global damages because they underestimate the benefits in polar regions and overestimate the damages in tropical regions compared to the GCM predictions.     

Environmental impacts of climate change adaptation

Climate change adaptation reduces adverse effects of climate change but may also have undesirable environmental impacts. However, these impacts are yet poorly defined and analysed in the existing literature. To complement this knowledge-gap, we reviewed the literature to unveil the relationship between climate change adaptation and environmental impact assessment, and the degree to which environmental impacts are included in climate change adaptation theory and practice. Our literature review showed that technical, social and economic perspectives on climate change adaptation receive much more attention than the environmental perspective. The scarce interest on the environmental impacts of adaptation may be attributed to (1) an excessive sectoral approach, with dominance of non-environmental perspectives, (2) greater interest in mitigation and direct climate change impacts rather than in adaptation impacts, (3) a tendency to consider adaptation as inherently good, and (4) subjective/preconceived notions on which measures are good or bad, without a comprehensive assessment. Environmental Assessment (EA) has a long established history as an effective tool to include environment into decision-making, although it does not yet guarantee a proper assessment of adaptation, because it is still possible to postpone or even circumvent the processes of assessing the impacts of climate adaptation. Our results suggest that there is a need to address adaptation proactively by including it in EA, to update current policy frameworks, and to demand robust and reliable evaluation of alternatives. Only through the full EA of adaptation measures can we improve our understanding of the primary and secondary impacts of adaptation to global environmental change.     

Participatory integrated assessment of adaptation to climate change in Alpine tourism and mountain agriculture

Winter tourism and mountain agriculture are the most important economic sectors in a major part of the Swiss Alps. Both are highly sensitive to changing climatic conditions. In the framework of the CLEAR project, results from climate impact research in the field of tourism and agricultural production were used to investigate the perception of climatic change by stakeholders and to assess possible adaptations. We used a participatory integrated assessment (PIA) to involve the knowledge, values and experiences of the various social actors in tourism and agriculture (e.g., skiers, tourism managers, farmers) in the research process. Whereas climate change may have various severe direct impacts on the tourism industry, depending on the region, agricultural production may generally benefit from changed climatic conditions. But because of the dependence of farmers on “off-farm” income, the loss due to declining winter tourism in specific areas may cause more important indirect effects. However, the two sectors may adapt actively by choosing from a variety of strategies, and the loss of income from the tourism industry may support the re-evaluation of the various functions agriculture plays in mountain regions, beyond the production of food. The study demonstrates the suitability of the PIA approach to elucidate the interactions between different stakeholders and their perception of the climate change phenomena. A similar participatory approach could be a useful tool to transfer research results and expert knowledge to the political process addressing adaptations to climate change. This revised version was published online in July 2006 with corrections to the Cover Date.     

global climate change: processes and products – an overview

Our knowledge of global climate change has many uncertainties.Whether global air temperature will increase, by how much, and when,are subject to debate, but there is little doubt that troposphericconcentrations of several trace gases are increasing. While possibleincreases in the average air temperature is a product of these changes,the increases in the trace gases alone will have an effect on agriculture.Increases in the ambient concentrations of carbon dioxide are expectedto have a positive net effect on crop production. In contrast, anyincreases in the penetration of surface-level ultraviolet-B (280–320 nm)radiation, and known increases in surface ozone concentrations, areconsidered to have adverse effects on certain crops. Our presentknowledge of the joint effects on crops of elevated levels of carbondioxide, ultraviolet-B radiation and ozone, and possible alterations in airtemperature and precipitation patterns, is virtually zero. Therefore, anypredictions of the effects of global climate change on agriculture aresubject to significant uncertainties. In contrast, coupling of climatechange (only temperature and precipitation) models to crop productionhas led to a number of future scenarios. In spite of theirpresent limitations, results from these efforts can be useful in planningfor future agriculture.     

A General Equilibrium Assessment of Climate Change Impacts on Swiss Winter Tourism with Adaptation

Winter alpine tourism has been repeatedly identified as one of the economic sectors most at risk from climate change in Switzerland. However, all of the costs that have been estimated so far for the Swiss tourism sector are, to some extent, misleading as they do not, or only partially, incorporate adaptation possibilities and general equilibrium effects. We attempt to fill this gap using a computable general equilibrium model that is specifically designed for the purposes of this research. Our modeling efforts first consist in creating a tourism sector with a part of it being dependent on snow. We also carefully model the snowmaking technology. Using climate change scenarios on future snow cover, we analyze their impacts on the Swiss ski industry. We find welfare effects for the Swiss economy ranging from − 23 to 113 million CHF in 2050. This range arises from the use of various assumptions concerning adaptation possibilities. We also show that geographical substitutions between international ski destinations have large positive effects for Switzerland. From a more general perspective, our results exemplify the risks of estimating the consequences of climate change based only on domestic impacts of climate change with no adaptation being implemented.

     

Using Temporal Coherence to Determine the Response to Climate Change in Boreal Shield Lakes

Climate change is expected to have important impacts on aquatic ecosystems. On the Boreal Shield, mean annual air temperatures are expected to increase 2 to 4°C over the next 50 years. An important challenge is to predict how changes in climate and climate variability will impact natural systems so that sustainable management policies can be implemented. To predict responses to complex ecosystem changes associated with climate change, we used long-term biotic databases to evaluate how important elements of the biota in Boreal Shield lakes have responded to past fluctuations in climate. Our long-term records span a two decade period where there have been unusually cold years and unusually warm years. We used coherence analyses to test for regionally operating controls on climate, water temperature, pH, and plankton richness and abundance in three regions across Ontario: the Experimental Lakes Area, Sudbury, and Dorset. Inter-annual variation in air temperature was similar among regions, but there was a weak relationship among regions for precipitation. While air temperature was closely related to lake surface temperatures in each of the regions, there were weak relationships between lake surface temperature and richness or abundance of the plankton. However, inter-annual changes in lake chemistry (i.e., pH) were correlated with some biotic variables. In some lakes in Sudbury and Dorset, pH was dependent on extreme events. For example, El Nino related droughts resulted in acidification pulses in some lakes that influenced phytoplankton and zooplankton richness. These results suggest that there can be strong heterogeneity in lake ecosystem responses within and across regions.     

Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa

The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.     

Dynamics of harmful dinoflagellates driven by temperature and salinity in a northeastern Mediterranean lagoon

To attempt to determine the effects of temperature and salinity on the dynamics of the dinoflagellate community, a monthly sampling was carried out from October 2008 to March 2009 at eight sampling stations in Ghar El Melh Lagoon (GML; Mediterranean Sea, Northern Tunisia). Dinoflagellates were dominant among plankton, accounting for 73.9 % of the lagoon’s overall plankton community, and were comprised of 25 different species among which 17 were reported in the literature as harmful. While no significant difference was found in the distribution of dinoflagellates among the stations, a strong monthly difference was observed. This temporal variability was due to an increase in the abundance of Prorocentrum micans from December to February, leading to a strong decrease in the Shannon diversity index from station to station. At the onset of P. micans development, dinoflagellate abundances reached 1.26.10⁵ cells l^?1. A redundance analysis indicates that both temperature and salinity have a significant effect on the dynamics of the dinoflagellate community. Using a generalized additive model, both temperature and salinity appear to have significant nonlinear relationships with P. micans abundances. Model predictions indicate that outbreaks of P. micans may occur at a temperature below 22.5 °C and with salinity above 32.5. We discuss our results against a backdrop of climate change which, by affecting temperature and salinity, is likely to have an antagonistic impact on P. micans development and subsequently on the dinoflagellate dynamics in GML.     

Assessment of anthropogenic threats to Chilean Mediterranean freshwater ecosystems: Literature review and expert opinions

Anthropogenic threats and their impacts on aquatic ecosystems have traditionally been evaluated only through literature reviews. Within the last decade, however, expert opinions have become an increasingly popular alternative for gaining complementary information to literature reviews. This study employed a standardized method for collecting bibliographic data combined with synthesize expert opinions to establish a current knowledge baseline on threats to Mediterranean freshwater ecosystems in Chile.We revised 79 scientific articles that included a variety of taxonomic groups containing fish (n = 32); macroinvertebrates (n = 17); amphibians (n = 18); freshwater plants (n = 8); and two taxonomic groups simultaneously (n = 4). From this review, we identified 14 threats, with land-use change, species introductions, and industrial/domestic effluents as salient factors. These findings were in agreement with results from expert opinion surveys (n = 46 researchers). An analysis by taxonomic group indicated freshwater fishes as most threatened by hydropower plants. Aquatic plants were most threatened by mining. Amphibians were most threatened by changes in soil use whereas aquatic macroinvertebrates by industrial/domestic effluents. Remarkably, the magnitude of threats identified in the literature review was of similar order than those catalogued by experts. Moreover, the primary threats identified here align with those reported in other Mediterranean regions of the world. Our combined approach using literature review and expert opinion was useful in determining the consistency of the main threats to each taxonomic group. Our findings can be used as a baseline to further research and in prioritizing management strategies for threatened Mediterranean ecosystems worldwide.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

Effects of Temperature–Climate Patterns on the Production of Some Competitive Species on Grounds of Modelling

Climate change has serious effects on the setting up and the operation of natural ecosystems. Small increase in temperature could cause rise in the amount of some species or potential disappearance of others. During our researches, the dispersion of the species and biomass production of a theoretical ecosystem were examined on the effect of the temperature–climate change. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during modelling a theoretical ecosystem, and several important theoretical questions could be answered.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

Assessing the impact of multiple drivers of land sensitivity to desertification in a Mediterranean country

Experiencing climate changes and increased human pressure, Mediterranean regions are considered representative hotspots of desertification. However, relatively few studies have been devoted to quantify the individual impact of different factors shaping land sensitivity to desertification in these contexts. Our study contributes to this deserving (positive and normative) issue with a diachronic analysis of the impact of multiple drivers of desertification risk on six indicators of land sensitivity based on the Environmentally Sensitive Area (ESA) approach. Indicators (average and maximum ESA score, coefficient of variation and normalized range in the ESA scores, share of ‘fragile’ and ‘critical’ areas in total landscape) were calculated in 777 rural districts of Italy at three time points (early-1960s, early-1990s, and early-2010s). Multivariate models were used to determine the impact of 12 predictors (climate, soil, vegetation, and land management quality) on each indicator of land sensitivity. Results of the analysis identified two non-redundant dimensions respectively associated with the average level of land sensitivity and its intrinsic variability across space. Impacts of climate and vegetation qualities on the level of land sensitivity were high, decreasing over time, and more intense respectively in Northern and Southern Italy. Impacts of soil and land management qualities were moderate, increasing over time, and involving almost all the country's area. Our study emphasizes the role of context-based measures promoting sustainable land management. The ‘local’ dimension proved to be crucial in any strategy of risk mitigation undertaken at disaggregated spatial scales.     

Climate change impact on the olive pollen season in Mediterranean areas of Italy: air quality in late spring from an allergenic point of view

Recent studies have shown that there are many effects of climate change on aeroallergens, and thus on allergic diseases in humans. In the Mediterranean region, despite the importance of the olive tree for production, there is high allergenicity of olive pollen and related risks to human health. Aerobiological sampling techniques can be used to analyse the pollinosis phenomenon through determination of mean daily pollen concentrations per cubic metre of air. The present study was carried out from 1999 to 2008 in 16 olive-growing areas in Italy, to update the information on the pollinosis characteristics of Olea europaea in the study areas. The analysis of the average flowering season over the study period highlights a temporal scaling of pollen in the atmosphere that depends on the different climatic characteristics. This is mainly dependent on temperature, and in part, determined by latitude. Generally, the levels of O. europaea pollen in the atmosphere are higher from mid-April to the end of June, with the period of greatest risk to human health due to this olive pollen in this area currently limited primarily to the last 10 days of May. However, the pollen season can move, depending on the climate scenario considered, and data here can be used to determine potential time shifts in pollinosis that might cause more precocious asthma and allergy problems. The allergy season for this type of pollen might be significantly precocious in future decades (20–30 days earlier in the year), which will impact on the severity and duration of allergies attributable to olive tree pollen.     

Estimating the probability of wildfire occurrence in Mediterranean landscapes using Artificial Neural Networks

Wildfires are a major disturbance in the Mediterranean Basin and an ecological factor that constantly alters the landscape. In this context, it is crucial to understand where wildfires are more likely to occur as well as the drivers guiding them in complex landscapes such as the Mediterranean area. The objectives of this study are to estimate wildfire probability occurrence as a function of biophysical and human-related drivers, to provide an assessment of the relative impact of each driver and analyze the performance of machine learning techniques compared to traditional regression modeling. By employing an Artificial Neural Network model and fire data (2004–2012), we estimated wildfire probability across two geographical regions covering most of the Italian territory: Alpine and subalpine region and Insular and peninsular region. The high classification accuracy (0.68 for the Alpine and subalpine region and 0.76 for the Insular and peninsular region) and good performances of the technique (AUC values of 0.82 and 0.76, respectively) suggest that our model can be used in the areas studied to assess wildfire probability occurrence. We compared our model with a logistic function, which showed a weaker predictive power (AUC values of 0.78 for the Alpine and subalpine region and 0.65 for the Insular and peninsular region) compared to the Artificial Neural Network. In addition, we assessed the importance of each variable by isolating it in the model. The importance of an individual variable differed between the two regions, underscoring the high diversity of wildfire occurrence drivers in Mediterranean landscapes. Results show that in the Alpine and subalpine region, the presence of forest is the most important variable, while climate resulted as being the most important variable in the Insular and peninsular region. The majority of areas recently affected by large wildfires in both regions have been correctly classified by the ANN model as ‘high fire probability’. Hence, the use of an Artificial Neural Network is efficient and robust for understanding the probability of wildfire occurrence in Italy and other similar complex landscapes.     

Analysing Seasonal Differences between a Soil Water Balance Model and in Situ Soil Moisture Measurementsat Nine Locations Across Europe

We compared soil moisture from the soil water balance model for European Water Accounting (swbEWA) with in situ observations from nine locations in three European climatic zones (continental, Mediterranean and maritime temperate), for different periods between 2003 and 2011. Despite the simplicity of the swbEWA model, the patterns of temporal changes in soil moisture content are well represented at all locations. Annual averages show that the model overestimates the soil moisture content, and that overestimations are the smallest when measurements are obtained from more than one depth. These results suggest that the relationship between simulated and observed soil moisture also depends on the number of measurements and the depth over which they are taken. In the continental climate, where snow cover and frozen soil influence soil moisture, we observe higher root mean square error values in winter months. However, in the Mediterranean and maritime temperate climates, we do not observe clear common seasonal patterns in the soil moisture profile, which makes it difficult to relate the model’s accuracy to climate. With the percentage of correctness and probability of detection measures, we tested the model performance in simulating dry versus non-dry events. The percentage of the correctly classified dry and non-dry events is higher than 84 % at all locations, whereas the probability to detect dry events is significantly lower, exceeding 50 % at only four out of nine stations. The frequency distribution of consecutive days with dry soil (CDDS) confirms the model performance: higher number of short dry periods (with less than 20 days of soil moisture near wilting point) are reproduced and observed in continental climates, whereas long dry periods (longer than 50 days) are noted in the Mediterranean climate. Overall, the statistical measures suggest that the model produces the highest accuracy in summer months at the stations in continental climates, whereas in the Mediterranean climate, the accuracy is slightly higher in the colder seasons.     

Lake ecosystem responses to rapid climate change

In this paper, we examine the consequences of rapid climate change on lake ecosystems in terms of two main effects: variability effects and magnitude effects. How these factors influence life history selection is considered by focusing upon body size as a quantifiable and strong correlate of life history variation (Pianka 1970, McNab 1980, Charnov 1991). We then consider the relationship between the concept of biological diversity and the diversity of life history strategies in the context of rapid climate change.     

An integrated assessment modeling framework for assessing primary and secondary impacts from carbon dioxide stabilization scenarios

As the nations of the world negotiate future controls on greenhouse gas emissions, a critical environmental policy issue becomes understanding the multiple environmental consequences of these controls. Here we describe an integrated assessment model for quantifying multiple environmental impacts of large-scale environmental initiatives and apply this model to climate change mitigation. Our analysis shows that reductions in global warming will be accompanied by reductions in ozone depletion, acid rain and mercury emissions, and desulfurization waste generation. We also conclude that the largest collateral benefits from reducing global climate change may be in the developing world. This result is critical since it is the developing nations who ultimately control the long-term success of any climate stabilization strategy. This revised version was published online in July 2006 with corrections to the Cover Date.